Optimizing game live service for mobile free-to-play games

In this paper, we propose a method for optimizing the game live service. Especially, we focus on improving user retention. Firstly, we define player churn in the game and extract features that contain the properties of the player churn from the game logs. And then we evaluate the importance of features using random forest in classification. Finally, we build association matrix between features and suggest a reward method for in-game events according to the relative importance of features and the interrelationships between features. Results of applying to the game in service show that the proposed scheme is enough to improve user retention.